The present inventions relate to methods of characterising ventricular operation. In particular, but not exclusively, they relate to a system for quantifying abnormalities of an electrocardiogram and to a method and an apparatus for measuring such abnormalities. The present inventions also extend to an operating system for a computer, to a computer program and to media having stored thereon a computer program for putting the inventions into effect. Other applications include use of the algorithms in pacemakers and heart monitors. The inventions share a common link of characterising differences in the wavefront of the repolarisation wave.
Electrocardiographic patterns of the heart""s movements have been well studied. An electrocardiogram (ECG) records the changes in electrical potential associated with the spread of depolarisation and repolarisation through the heart muscle. In a normal healthy patient, depolarisation starts in an area of the right atrium called the sinoatrial node and spreads through the atrioventricular node and into the ventricular muscle via specialised conduction tissue, causing the two atria and the two ventricles to contract. During repolarisation, the atria and ventricles relax and refill with blood. The depolarisation of the atria is responsible for the P wave of an ECG and depolarisation of the ventricles results in the QRS complex. Repolarisation of the atria coincides with the QRS complex so it is not seen. Repolarisation of the ventricles, however, is seen as the T wave.
ECG""s are typically recorded using a standard arrangement of 12 leads, 6 (the I, II, III, VR, VL, VF leads) looking at the heart in different directions in an approximately vertical plane of a body in an upright position and 6 (the V1, V2, V3, V4, V5 and V6 leads) looking at the heart in different directions in an approximately horizontal plane. Using such an arrangement of leads, the spread of the waves of electrical potential associated with depolarisation and repolarisation through the three dimensional space of the body, can be recorded.
The spread of these waves through the heart is often described by vectors. For example, the average direction of spread of the depolarisation wave through the ventricles as seen from the front of the body is called the cardiac axis and the direction of this axis has long been used to indicate different abnormalities of the heart.
To study abnormalities associated with ventricular repolarisation, a number of data processing techniques have been proposed to measure, for example, the QT interval, i.e. the interval between the beginning of depolarisation and the end of repolarisation of the ventricles. Interlead variability of the QT interval durations in standard 12 lead ECG recordings has also been studied. However, whilst these measurements may provide some diagnostic assistance, concerns have been raised about the poor reproducibility of results.
Studies have also tried to quantify the inhomogeneities in the ventricular repolarisation patterns by evaluating the complexity of the T wave morphology using eigenvalues associated with the principal components of ECG, measured over a period of 24 hours. The direction of the ECG vector during T wave in the 3D physical (x,y,z) has also been shown to have some predictive value.
However, there is still a need for further measurements which may provide a more accurate technique for identifying certain conditions, particularly those which affect repolarisation of the ventricles. A problem with known methods, for example, is that they only quantify global variations in the T wave rather than spatial variations in individual waves, that is the synchronicity of the T wave, as observed from different locations on the body, is not observed.
Thus, viewed from a first broad aspect, a first invention described herein provides a method of quantifying abnormalities of an electrocardiogram observing repolarisation patterns from different locations on a body, wherein the abnormalities are quantified by a measure of the synchronicity of the repolarisation patterns as observed from those different locations on the body. In other words, this is a measure of the homogenity of the spread of repolarisation waves.
Unlike depolarisation of the heart muscle, the repolarisation of individual cells is not triggered by neighbouring cells but is instead a time dependent process. If repolarisation patterns, as observed in different locations on the body, lack synchronicity, then this can be indicative of certain heart complications.
By quantifying these abnormalities, it may be possible to use the data to assist with diagnosis or to identify patients at most risk or classify them into different categories of risk. This may be of great importance in determining whether certain treatments should be offered to a patient, for example. The data could also be used to trigger an alert in a monitoring device.
The homogenity of the spread of repolarisation waves can be measured by quantifying the spatial variability of the ventricular repolarisation patterns i.e. the spatial variability of the T wave.
Thus viewed from a second aspect, the first invention provides a method of characterising ventricular operation, comprising the steps of:
recording a signal monitoring the propagation of a repolarisation wave;
determining a vector which is representative of the wavefront of the repolarisation wave; and
determining a measure of the spatial variation of the repolarisation wavefront.
In one preferred embodiment, it provideed a method of quantifying abnormalities of ventricular repolarisation by determining a measure of the spatial T wave morphology variation.
Preferably the spatial T wave morphology variation is quantified by measuring the T wave Morphology Dispersion.
Preferably this is achieved by determining vectors describing the contributions which the signals from each lead (often referred to as the channels of an ECG) makes to the T wave. The angles between these vectors are then calculated and a mean value is determined. This mean value of the angles provides a measure of the spatial T wave morphology variation. The smaller the value, the closer the T wave morphologies will be in the signals of the individual leads.
Preferably the ECG signal is morphologically filtered to improve the signal to noise ratio. In one preferred embodiment, this consists of the steps of decomposing the T wave using a technique such as Singular Value Decomposition, filtering by keeping only the two most significant signal components, and applying a DC compensation. A preferred DC compensation is provided by subtracting an average of the start and end signal components during the QRS complex and T wave. The morphologically filtered T wave is then preferably rescaled to equalise energies in the different component directions. The corresponding reconstruction parameters are calculated to determine the vector contributions of each of the ECG leads. The angles between each pair of the vector contributions is then calculated and the mean determined. Most preferably the contribution in respect of lead V1 is ignored because the T wave morphology in this lead is generally different than that of other channels, irrespective of any clinical background, mainly due to the position of the V1 electrode, and by ignoring this component, it has the effect of enhancing the predictive value of the T wave morphology dispersion descriptor.
The main reason for initially decomposing the data matrix is to find an optimum representation of the ECG signals upon which the measurements can be performed. In this way, the system does not use the standard XYZ axes of the body but finds an optimally constructed orthogonal system to represent the 12 lead ECG. In a preferred embodiment, therefore, the first invention can be seen as providing a method for looking at the vector representation of each of the standard electrocardiographic leads in an optimum dimensional vector space in which the ECG signals can be represented and comparing the angles between the vectors of individual standard leads.
The spatial T wave morphology variation may provide a useful descriptor when it is determined for the whole of the T wave, the first half of the T wave, the second half of the T wave or any other portion or combination of portions of the T wave.
The present inventions are not limited to standard 12 lead electrocardiograms, although this is preferred, but extend to electrocardiograms produced from only three or more leads. In certain applications, it may be useful to use the electrodes of a pacemaker to record an electrocardiogram signal. In such situations, the positions and numbers of the electrodes would not usually correspond with the arrangement of standard leads, for example. Whilst it is preferred to view the waves in three dimensions, because, research up to date suggests that approximately 99% of 12-lead ECG energy can be represented in a 3D space, the inventions are applicable to situations where the heart is viewed in any dimensions, greater than or equal to two.
In a conventional 12 lead ECG, only 8 (I, II, V1, V2, V3, V4, V5 and V6) of the signals are independent. The other 4 signals (III, VR, VL, VF) are algebraically dependent on the other leads so, if desired, may be generated by data processing methods rather than measured as such. As explained above, it is most preferred to use signals only from leads I, II, V2, V3, V4, V5 and V6, and to ignore the signal from V1 in order to concentrate the abnormalities seen in the T wave. The position of the leads, although having an effect on the value produced by the descriptors, is not critical to the inventions. Whilst the inventions may be described with reference to the standard ECG leads, this is not intended to limit the inventions to just those positions. These positions are preferred, however, since they have become xe2x80x9cstandardxe2x80x9d measuring points throughout the world.
It has also been found that comparing the spread of depolarisation through the ventricles with the spread of repolarisation can provide useful information.
Thus, in accordance with a first aspect of a second invention described herein, there is provided a method of characterising ventricular operation, comprising the steps of:
recording a signal monitoring the propagation of depolarisation and repolarisation waves;
determining vectors which are representative of the direction of the wavefronts of the depolarisation and repolarisation waves; and
determining a measure of the deviation between those vectors.
Thus, the present invention can be seen to provide a method of quantifying abnormalities of an electrocardiogram observing the spread of depolarisation and repolarisation waves through the ventricles, wherein the abnormalities are quantified by comparing a property of the depolarisation wave with a property of the repolarisation wave where preferably the abnormalities are quantified by a measure of the vector deviation between the ventricular depolarisation and the ventricular repolarisation waves.
Described in other terms, a method of the second invention may compare the direction of the depolarisation wave (i.e., the QRS part of the ECG) with the repolarisation wave (i.e. the T wave). This may be achieved by comparing the angles between principal vectors of the ventricular depolarisation and repolarisation waves, comparing the angles between a principal vector of the ventricular depolarisation wave and the ECG vectors during ventricular repolarisation, comparing the angles between the ECG vectors during ventricular depolarisation and a principal vector of the ventricular repolarisation wave, or comparing the angles between the ECG vectors during ventricular depolarisation with those during ventricular repolarisation. The angles may be compared for the whole of a wave or just a portion of a wave or any combination of portions of the waves. For example, in one embodiment the angles between the depolarisation and repolarisation vectors are compared for portions of the waves which span the peak energy values, but it may be preferred in some instances to look at and compare other portions of the waves which would correspond to depolarisation and repolarisation occurring in different regions of the heart muscle.
Preferably the vector deviations are determined using the optimally constructed representation of the ECG signals discussed above.
In healthy patients, the principal vectors would, generally speaking, only deviate by up to about 30xc2x0. In patients having hypertropic cardiomyopathy (HCM), for example, vector deviations greater than 90xc2x0 may be seen. These deviations can be distinguished over inversion of the T wave, for example, which would result in angles closer to 180xc2x0.
Again it is preferred to conduct certain data processing steps before the angles of the vectors describing the QRS complex and T wave are compared. Firstly the data matrix describing the signal is decomposed, again preferably by Singular Value Decomposition. The decomposed signal components are ranked in order of their significance in terms of the energy of the ECG vector that they represent. Thus the First signal component contains the most energy in a first direction. The second signal component contains the next most energy in a second direction which is perpendicular to the first. The third signal component contains the next most energy in a third direction which is perpendicular to the first and second directions. Where eight of the independent ECG channels are recorded, the ECG vector can be decomposed into an eight dimensional orthogonal space. When measuring the vector deviations of depolarisation and repolarisation vectors, a good approximation may be made by only measuring the first two or three of the decomposed signal components since these can account for more than 99% of the total energy of the 12-lead ECG signal. The QRS complex and T wave are localised by making use of the variation of the instantaneous ECG energy. The method does not depend on accurate localisation of the QRS complex and the T wave. This method of detection provides an example of many possible ways.
Both the vector representations of the QRS complex and T wave follow an approximate loop in the constructed space. Vectors can be determined which represent the maximum energy of the T wave and QRS complex, and the angles between them compared. More preferably a vector describing the maximum energy of the T wave is compared to the vectors describing the QRS complex for a set of points at the peak of ventricular repolarisation (which, for example, can be determined by tracing the instantaneous ECG energy). In the most preferred embodiment, the vector deviation between the depolarisation and repolarisation waves is measured as the average of the cosines of the angles between the vector describing the maximum energy of the T wave and the vector describing the wavefront of the QRS complex, the angles being determined in constructed space. The measurement of the vector deviation in terms of the cosine of the angle is referred to herein as TCRTxe2x80x94total cosine R_to _T.
The second invention introduces the idea of considering depolarisation and repolarisation processes of the heart muscle simultaneously and comparing them. While it may be described as a comparison of ECG vectors observed during these processes, in an appropriately constructed vector space, this is not intended to limit the invention to just ECG vector comparison and to processing of standard ECG leads.
Comparing the propagation directions of depolarisation and repolarisation has revealed some interesting detection properties. In particular, TCRT has proved to be more sensitive to autonomic changes of ventricular repolarisation than other known descriptors such as ventricular gradient and QT dispersion. From investigations, it has been found that TCRT responds quickly to changes in the position and activity of the patient with distinct ranges or levels of descriptor values being obtainable for different autonomic tones. This descriptor may be used to check for abnormalities in ventricular depolarisation and repolarisation under different autonomic conditions, thereby providing a fuller picture to assist with diagnosing defects. TCRT has been found to be useful as a predictor for mortality in patients which have suffered acute myocardial infarction and as a predictor for arrythmias. The descriptor could be used in a monitor carried by the patient or in equipment in an intensive care unit to warn the patient or medic by means of an alarm when the TCRT is pushed to a danger level as a result of changes in the autonomic tone, for example, caused through exercise or trauma. TCRT could also be used to check that the patient has a properly functioning autonomic system, for example, prior to the administration of anaesthetic agents before surgery.
TCRT is in effect able to provide a measure of the autonomic tone of a patient. It could be used to control pacing of a pacemaker making it more responsive to the patient""s needs by responding to changes in the autonomic tone. TCRT is increased by physical or emotional stress during fixed rate pacing and is decreased by an increase in pacing rate. TCRT could be implanted in a closed loop rate-adaptive feedback system. At times of physical or emotional stress TCRT would increase, triggering an increased pacing rate to decrease TCRT to resting level.
TCRT could be used to monitor the effect of certain drugs and the way in which they effect the autonomic system. When testing drugs which prolong the QT interval, TCRT could be used to monitor the patient and raise an alarm arrythmias are predicted or detected. It could be used to monitor changes in electrolyte of the body and other conduction phenonoma. It could even be used to control a drug delivery mechanism, administering certain drugs as heart function abnormalities are detected or in response to changes in the autonomic tone.
Conditions such as ischemia, as well as most illnesses, will have an effect oil the autonomic tone of the patient. TCRT could be used to assist in the prediction of ischemia or in the monitoring of the progression of a disease, for example, in heart failure patients, by providing an indication of the autonomic tone as well as changes in direction of the repolarisation wavefront. TCRT may be able to observe autonomic changes caused by the onset of ischemia before ST segment changes are observable on an ECG or pain is felt by the patient. It may also be useful in the monitoring of patients suffering from epilepsy, providing an early warning of heart function abnormalities. The autonomic tone could be observed to detect hypoxy conditions in a patient prone to fitting.
It should be noted that the possibilities mentioned above with reference to TCRT are not intended to be inferred as limiting the present invention to the preferred situation where TCRT is the average of the cosines of the angles between the vector describing the maximum energy of the T wave and the vector describing the wavefront of the QRS complex. For example, TCRT may compare the angles between the sets of vectors describing the depolarisation and repolarisation wavefronts with respect to time or may compare the vectors describing the maximum energy of depolarisation and repolarisation to each other. While the use of cosine provides an effective way of separating the angles between the vectors associated with abnormalities from those observed in normal patients, other operators may be used to separate the data.
As mentioned above, of the standard 12 lead ECG signals, 8 are independent. Thus, it is possible to describe the T wave as an 8-by-n matrix M, with each row corresponding to a standard ECG channel (I, II, V1, V2, V3, V4, V5, V6) and n being the number of samples. Performing Singular Value Decomposition on the matrix M generates a signal vector representing the progress of a T wave in 8 dimensions, where each dimension can be regarded as a component of the signal, associated with a fraction of the total energy of 12-lead ECG. For most purposes, as mentioned above, only the first two or three components are normally used, since these may account for over 99% of the total T wave energy in 12-lead ECG signals. However it has been found that comparing the energy of the most significant components with the energy of the other components provides a further useful descriptor that can be used during analysis of the ECG.
Thus according to a third invention described herein, there is provided a method of quantifying abnormalities of an electrocardiogram having a plurality of independent signals, in which the signals are decomposed to obtain a signal vector having two or more signal vector components, wherein the energy of the components is compared.
Preferably, the components are arranged substantially in order of decreasing signal energy and the energy of the most significant components representing the majority of the signal energy is compared to the energy of the other components. Preferably the electrocardiogram records 8 independent signals and the signal vector has 8 components and the first 3 components of the signal vector, thus constructed, represents the majority of the signal energy.
The third invention introduces the idea to transform the ECG signals into an optimally constructed space which represents the ECG energy in a minimum dimensional space of orthogonal components and to assess the residual energy that is left outside the three dimensional space of the first three signal components. In a possible implementation, as described above, this corresponds to assessing the relative values of the 3 highest singular values of the matrix M to the other singular values. The first three signal components represent the dipolar components of the ECG vector and the remaining signal components correspond to the non-dipolar components. By measuring the power in the orthogonal components outside the three dimensional space, it is possible to measure the power of the non-dipolar components which provides a measure of the local repolarisation abnormalities. However with a different set of input signals and/or different parts of the ECG signal, the separation/number of significant components may vary.
The inventions described above also extend to an apparatus which is programmed with an algorithm to process data from an ECG in accordance with any of the described inventive methods. The apparatus could be a computer, for example, programmed in a particular way or could be a plug-in box for an ECG apparatus or an ECG apparatus provided with means to calculate these descriptors and display the result to an operator. Furthermore, the inventions extend to an operating system or a computer program having an algorithm to process data from an ECG in accordance with the described methods and to media having such a computer program or operating system stored thereon. Thus, the inventions extend to a computer program product which is directly loadable into the internal memory of a digital computer, comprising software code portions for performing the steps of the afore-described methods when the product is run on a computer.
The present inventions will now be described by way of example only with reference to a preferred embodiment and the accompanying drawings, in which: